Object-based multispectral image fusion method using deep learning

Hyunsung Jang; Namkoo Ha; Yoonmo Yeon; Kuyong Kwon; Sungho Gil; Seungha Lee; Sungsoon Park; Hyungjoo Jung; Kwanghoon Sohn

doi:10.1117/12.2532718

19 September 2019 Object-based multispectral image fusion method using deep learning

Hyunsung Jang, Namkoo Ha, Yoonmo Yeon, Kuyong Kwon, Sungho Gil, Seungha Lee, Sungsoon Park, Hyungjoo Jung, Kwanghoon Sohn

Author Affiliations +

Proceedings Volume 11169, Artificial Intelligence and Machine Learning in Defense Applications; 111690O (2019) https://doi.org/10.1117/12.2532718
Event: SPIE Security + Defence, 2019, Strasbourg, France

Abstract

The goal of multispectral image fusion is to integrate complementary information from multispectral sensors to enhance human visual perception and object detection. Additionally, there are also cases when only the object needs to be emphasized with minimal background interference. This paper presents an object-based fusion method using deep learning to accomplish this objective. The proposed method uses information regarding the region of an object to perform fusion on the object. As we cannot provide labels for fusion results at the learning stage, we propose an unsupervised learning method. The proposed method simultaneously provides appropriate image information from the background and target for surveillance and reconnaissance.

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Hyunsung Jang, Namkoo Ha, Yoonmo Yeon, Kuyong Kwon, Sungho Gil, Seungha Lee, Sungsoon Park, Hyungjoo Jung, and Kwanghoon Sohn "Object-based multispectral image fusion method using deep learning", Proc. SPIE 11169, Artificial Intelligence and Machine Learning in Defense Applications, 111690O (19 September 2019); https://doi.org/10.1117/12.2532718

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KEYWORDS

Image fusion

Multispectral imaging

Image segmentation

Target detection

Sensors

Surveillance

Visualization

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